Fruit Disease Research Articles

Fruit Disease Identification using Image Processing Techniques and Feature Extraction

The detection and classification of fruit diseases using image processing is an important field of research in agriculture. This technology can help farmers quickly and accurately identify diseased fruits and take appropriate measures to control the spread of the disease. The proposed system involves capturing images of fruits using a camera, followed by processing and analysis of these images to detect and classify the type of disease present. The images are first pre-processed to remove noise and enhance their quality, after which they are segmented to identify regions of interest. Various features such as color, texture, and shape are extracted from these regions, which are then used to classify the disease. Machine learning algorithms such as support vector machines (SVM), artificial neural networks (ANN), and decision trees are commonly used to classify diseases. The performance of these algorithms is evaluated based on metrics such as accuracy, precision, and recall. The proposed system has the potential to significantly reduce the time and effort required for disease detection and classification. This can help farmers to take timely and informed decisions to prevent the spread of the disease, ultimately resulting in increased crop yield and profitability.

Influence of Fruit Wounding on Subsequent Monilinia laxa Infection of Nectarines

Despite the fact that brown rot is the most economically important disease in stone fruits, the relationship between mechanical stress and infection has never been explored. Thus, to explore this connection, we carried out four experiments linking nectarine wounding and M. laxa infection. First, we evaluated a possible systemic reaction of the fruit to wounding that could impact the M. laxa infection. Afterward, we study the impact of the fruit in the environment on M. laxa colonies grown in vitro. Subsequently, we tested the disease susceptibility of fruits inoculated with M. laxa placed in the same environment as wounded fruits. Finally, in the fourth experiment, the effect of wounding on the subsequent fruit infections was evaluated at three fruit stages. As a result, we observed that there was no evidence of a fruit systemic reaction to wounding and M. laxa infection. In the study related to the impact of the fruit in the environment of M. laxa, the findings suggest that M. laxa “perceived” the fruit’s presence, resulting in accelerated in vitro growth. Moreover, the presence of wounded fruits in the box increased the susceptibility to brown rot. Inoculated fruits showed a delayed and reduced infection 7 h after being wounded, during the second stage of fruit development (15–19 weeks after full bloom). Moreover, a red reaction associated with inoculation was detected immediately after the fruits were wounded. Nine phenolic compounds exclusively related to the red areas were extracted, while six other compounds were present in higher proportions. These compounds may be actively involved in plant–pathogen interactions and the activation of metabolic pathways involved in nectarine susceptibility/resistance to M. laxa.

Fungicidal activities of Cymbopogon winterianus against anthracnose of banana caused by Colletotrichum musae

The genus Cymbopogon (Poaceae) species have been widely cultivated throughout the world for a wide range of uses in the pharmaceutical and agricultural fields. The current work investigates the fungicidal activities of Cymbopogon winterianus extract (CWE) in controlling the C. musae that caused anthracnose disease in banana fruit. In vitro assay results showed that CWE at 1.5–2.5 gL−1 concentrations controlled the development of the test pathogen. Mycelial blast, cytoplasmic discharge, and spore edema were noticed when CWE was applied. The Minimum Effective Concentration (MEC) of CWE for the in vivo assay was 1.50 gL−1 and can be used as a postharvest treatment on banana fruit to deter anthracnose infection. Moreover, no visible phytotoxicity or changes in aroma were observed on banana fruit treated with CWE, even at the highest concentration of 2.5 gL−1. The GCMS analysis revealed 41 chemical components associated with CWE. The five main compounds were the following: Methyl oleyl ether (40.20%), γ-Sitosterol (15.80%), 6-Methylheptan-3-ol (7.13%), α-Terpineol (5.56%), and n-Pentadecanol (4.05%). The CWE possesses excellent fungicidal effects against C. musae; in the near future, it can be used as an alternative to commercially available traditional fungicides on the market.

Control of Bacterial Canker in Stone Fruit Trees by Chemical and Biological Products

Bacterial canker, caused by Pseudomonas syringae pv. syringae and pv. morsprunorum, is one of the most important diseases of stone fruit trees (Prunus spp.). The pathogen infects buds, flowers, fruitlets, leaves and shoots, from which the disease spreads to the branches, boughs and trunks, causing necrosis and cankers. The efficacy of different chemical and biological products for the control of bacterial canker on stone fruit trees was tested in 2018–2021. The experiments were conducted in sour cherry, plum and sweet cherry orchards in central Poland. Foliar application of the tested preparations was performed three times a season. The biological efficacy of the tested products in the control of bacterial canker was evaluated on sour cherry on the basis of infected leaves and fruits and on plum and sweet cherry on the basis of infected leaves. The highest efficacy was observed for products containing various forms of copper—copper oxide, copper oxychloride and copper hydroxide—as well as fertilizers with copper gluconate and the fungicide Luna Care 71.6 WG (fluopyram and fosetyl-Al). However, the biological preparations were significantly less effective. The conducted studies showed that preparations based on copper gluconate can be a valuable alternative to typical copper fungicides.

Identification and diagnosis of fruit diseases through image processing techniques

Identification and diagnosis of fruit diseases through image processing techniques

Preparation and potential of nanoparticles containing curcuminoids to control fungal diseases in tropical fruits

Colletotrichum species cause anthracnose in various tropical crops in both cultivation and postharvest periods. The current synthetic fungicides to treat anthracnose sometime show toxic effects for farmers, residues on foods, and environmental impacts. In this work, turmeric extract containing curcuminoids was used as an active ingredient and formulated into a nanoemulsion to control anthracnose in red pepper and tomato fruits. The nanoparticles containing turmeric extract (25 %) were successfully prepared by encapsulation using Tween-80 and PEG 400 as emulsifiers. Out of the three main curcuminoids in the turmeric extract, BDMC was determined as the most abundant constituent via HPLC analysis. Turmeric nanoparticles showed an average particle size of 203 nm, polydispersity index (PI) of 0.322, and zeta potential of -92.7 mV. In the in vitro antifungal bioassay, this nanoformulation significantly inhibited the mycelial growth of Colletotrichum gloeosporioides and Colletotrichum orbiculare in a dose-dependent manner. Red pepper anthracnose was also consistently suppressed by turmeric nanoparticles but the tomato anthracnose was resistant to this formulation at 10 mg/mL in vivo. The study results proved the effectiveness of turmeric nanoparticles to control red pepper anthracnose in postharvest preservation and suggested developing the innovative nanoformulation as a green fungicide.

Integrated Metabolome and Transcriptome Analysis Reveals a Potential Mechanism for Water Accumulation Mediated Translucency in Pineapple (Ananas comosus (L.) Merr.) Fruit.

A physiological disease of the pineapple fruit called pineapple translucency causes the pulp to become water-soaked, which affects the fruit's taste, flavor, shelf life, and integrity. In the present study, we analyzed seven pineapple varieties, of which three were watery and four were non-watery. There were no apparent macronutritional (K, P, or N) differences in their pulp, but the non-watery pineapple varieties had higher dry matter and soluble sugar content. The metabolomic analysis found 641 metabolites and revealed differential expression of alkaloids, phenolic acids, nucleotide derivatives, lipids, and other metabolites among the seven species. Transcriptome analysis and further KEGG enrichment showed downregulation of 'flavonoid biosynthesis' pathways, differential expression of metabolic pathways, secondary metabolites biosynthesis, plant-pathogen interaction, and plant hormone signal transduction. We believe this study will provide critical molecular data supporting a deeper understanding of pineapple translucency formation and greatly benefit future research on this commercially important crop.

Plant defensin MtDef4-derived antifungal peptide with multiple modes of action and potential as a bio-inspired fungicide.

Chemical fungicides have been instrumental in protecting crops from fungal diseases. However, increasing fungal resistance to many of the single-site chemical fungicides calls for the development of new antifungal agents with novel modes of action (MoA). The sequence-divergent cysteine-rich antifungal defensins with multisite MoA are promising starting templates for design of novel peptide-based fungicides. Here, we experimentally tested such a set of 17-amino-acid peptides containing the γ-core motif of the antifungal plant defensin MtDef4. These designed peptides exhibited antifungal properties different from those of MtDef4. Focused analysis of a lead peptide, GMA4CG_V6, showed that it was a random coil in solution with little or no secondary structure elements. Additionally, it exhibited potent cation-tolerant antifungal activity against the plant fungal pathogen Botrytis cinerea, the causal agent of grey mould disease in fruits and vegetables. Its multisite MoA involved localization predominantly to the plasma membrane, permeabilization of the plasma membrane, rapid internalization into the vacuole and cytoplasm, and affinity for the bioactive phosphoinositides phosphatidylinositol 3-phosphate (PI3P), PI4P, and PI5P. The sequence motif RRRW was identified as a major determinant of the antifungal activity of this peptide. While topical spray application of GMA4CG_V6 on Nicotiana benthamiana and tomato plants provided preventive and curative suppression of grey mould disease symptoms, the peptide was not internalized into plant cells. Our findings open the possibility that truncated and modified defensin-derived peptides containing the γ-core sequence could serve as promising candidates for further development of bio-inspired fungicides.

Research progress of volatile organic compounds produced by plant endophytic bacteria in control of postharvest diseases of fruits and vegetables

Pathogen infestation results in significant losses of fruits and vegetables during handling, transportation, and storage. The use of synthetic fungicides has been a common measure for controlling plant pathogens. However, their excessive use of chemicals has led to increased environmental pollution, leaving large amounts of chemicals in agricultural products, posing a threat to human and animal health. There is now an increasing amount of research activities to explore safer and more innovative ways to control plant pathogens. In this regard, endophytic bacteria contribute significantly. Endophytic bacteria are ubiquitous in the internal tissues of plants without causing damage or disease to the host. Due to their high volatility and difficulties in residue in fruits and vegetables, volatile organic chemicals (VOCs) produced by endophytic bacteria have received a lot of attention in recent years. VOCs are a potential biofumigant for the effective control of postharvest fruits and vegetables diseases. This review focuses mainly on the recent progress in using endophytic bacteria VOCs to control post-harvest fruits and vegetables disease. This review provides a brief overview of the concept, characteristics, and summarises the types, application effect, and control mechanisms of endophytic bacterial VOCs. The research area that is being developed has great application value in agriculture and living practice.

Reactive Oxygen Species Metabolism and Diacetoxyscirpenol Biosynthesis Modulation in Potato Tuber Inoculated with Ozone-Treated Fusarium sulphureum

Potato dry rot, caused by Fusarium species, is a devastating fungal decay that seriously impacts the yield and quality of potato tubers worldwide. Fusarium sulphureum is a major causal agent causing potato tuber dry rot that leads to trichothecene accumulation in Gansu Province of China. Ozone (O3), a strong oxidant, is widely applied to prevent postharvest disease in fruits and vegetables. In this study, F. sulphureum was first treated with 2 mg L-1 ozone for 0, 30 s, 1 min, and 2 min, then inoculated with the potato tubers. The impact of ozone application on dry rot development and diacetoxyscirpenol (DIA) accumulation and the possible mechanisms involved were analyzed. The results showed that ozone treatment significantly inhibited the development of potato tuber dry rot by activating reactive oxygen species (ROS) metabolism and increased the activities of antioxidant enzymes NADPH oxidase (NOX), superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) by 24.2%, 13.1%, 45.4%, and 15.8%, respectively, compared with their corresponding control. The activities of key enzymes involved in ascorbate-glutathione cycle (AsA-GSH) of ascorbic peroxidase (APX), dehydroascorbate reductase (DHAR), monodehydroascorbate reductase (MDHAR), and glutathione reductase (GR) also increased by 26.6%, 41.5%, 56%, and 24.1%, respectively, compared with the control group, and their corresponding gene expressions. In addition, ozone treatment markedly suppressed DIA accumulation in potato tubers by downregulating the expression of genes associated with DIA biosynthesis pathway. These results suggest that ozone treatment inhibited the occurrence of potato dry rot and the accumulation of DIA in potato tubers inoculated with F. sulphureum by promoting ROS metabolism and modulating DIA biosynthesis pathway.

Research on Artificial Intelligence based Fruit Disease Identification System (AI-FDIS) with the Internet of Things (IoT)

Monitoring fruit quality, volume, and development on the plantation are critical to ensuring that the fruits are harvested at the optimal time. Fruits are more susceptible to the disease while they are actively growing. It is possible to safeguard and enhance agricultural productivity by early detection of fruit diseases. A huge farm makes it tough to inspect each tree to learn about its fruit personally. There are several applications for image processing with the Internet of Things (IoT) in various fields. To safeguard the fruit trees from illness and weather conditions, it is difficult for the farmers and their workers to regularly examine these large areas. With the advent of Precision Farming, a new way of thinking about agriculture has emerged, incorporating cutting-edge technological innovations. One of the modern farmers’ biggest challenges is detecting fruit diseases in their early stages. If infections aren’t identified in time, farmers might see a drop in income. Hence this paper is about an Artificial Intelligence Based Fruit Disease Identification System (AI-FDIS) with a drone system featuring a high-accuracy camera, substantial computing capability, and connectivity for precision farming. As a result, it is possible to monitor large agricultural areas precisely, identify diseased plants, and decide on the chemical to spray and the precise dosage to use. It is connected to a cloud server that receives images and generates information from these images, including crop production projections. The farm base can interface with the system with a user-friendly Human-Robot Interface (HRI). It is possible to handle a vast area of farmland daily using this method. The agricultural drone is used to reduce environmental impact and boost crop productivity.

Essential Oils in Postharvest Treatment against Microbial Spoilage of the Rosaceae Family Fruits

Fruits undergo numerous chemical, physical, and microbiological changes during storage that shorten their postharvest life, reducing shelf-life and boosting food loss. Food quality and safety are seriously threatened by postharvest infections, one of the factors behind postharvest deterioration and mycotoxin contamination in fruits. The control of postharvest deterioration is a big concern because there are few management methods available. Several attempts have been undertaken to prevent the microbial degradation of fresh food at the postharvest stage without using synthetic fungicides, which are dangerous for the environment and people’s health. A good substitute for synthetic fungicides among them is the use of natural plant compounds, such as essential oils included or not included in the edible coatings. This review’s aim was to collect information from the scientific literature on the biological activity of essential oil, with or without edible coatings, against pathogens that cause the postharvest spoilage of many fruit belonging to Rosaceae family in order to develop appropriate substitute tactics for synthetic fungicides in the treatment of postharvest fruit diseases. Advances and obstacles surrounding emerging methods that may be useful for enhancing the effectiveness and dependability of essential oils were evaluated.

Study of the competition between Colletotrichum godetiae and C. nymphaeae, two pathogenic species in olive

Olive anthracnose, a critical olive fruit disease that adversely impacts oil quality, is caused by Colletotrichum species. A dominant Colletotrichum species and several secondary species have been identified in each olive-growing region. This study surveys the interspecific competition between C. godetiae, dominant in Spain, and C. nymphaeae, prevalent in Portugal, to shed light on the cause of this disparity. When Petri-dishes of Potato Dextrose Agar (PDA) and diluted PDA were co-inoculated with spore mixes produced by both species, C. godetiae displaced C. nymphaeae, even if the percentage of spores in the initial spore mix inoculation was just 5 and 95%, respectively. The C. godetiae and C. nymphaeae species showed similar fruit virulence in separate inoculations in both cultivars, the Portuguese cv. Galega Vulgar and the Spanish cv. Hojiblanca, and no cultivar specialization was observed. However, when olive fruits were co-inoculated, the C. godetiae species showed a higher competitive ability and partially displaced the C. nymphaeae species. Furthermore, both Colletotrichum species showed a similar leaf survival rate. Lastly, C. godetiae was more resistant to metallic copper than C. nymphaeae. The work developed here allows a deeper understanding of the competition between C. godetiae and C. nymphaeae, which could lead to developing strategies for more efficient disease risk assessment.

Multi-Scale Region-Of-Interest based Deep Learning for fruit disease identification and classification

Agricultural productivity is mainly affected by the different types of fruit diseases. To reduce such impacts, automated fruit disease identification and categorization model is vital. So, a Multi-scale Deep Learning (MDL) model was designed to identify and categorize the variety of strawberry fruit diseases. This model has an Adaptive Receptive Field Module (ARFM), a Bottleneck Block (BB), Depth-wise Residual Blocks (DRBs) and the Squeeze Excitation Residual Network (SE-ResNet) units to extract the Feature Maps (FMs) related to all disease classes. But, this model cannot partition individual fruit samples. Also, the number of fruits with multiple infections within a particular image was not easily captured. So, this article develops a Multi-scale Region-Of-Interest (ROI)-based DL model called (MRDL) to improve the accuracy of identification and categorization of a single fruit sample with a certain disease in a real-time scenario. This model is performed in 2 different phases. First, more robust features are extracted by the DRB, ARFM, and BB in the initial phase. Then, an ROI Fused (ROIF) unit, the SE-ResNet unit, a classification unit, and a mask unit are involved in the second phase. The ROIF unit obtains the FMs for all candidate ROIs using the candidate bounding boxes from the initial phase. The extracted FMs per sampled position are aggregated to get the fused FM, which is resized by integrating the attention strategy with the SE-ResNet unit. Those resized fused FMs are independently passed to the classification and mask units to classify the candidate bounding boxes and localize the infected pixels in the candidate ROIs, respectively. Finally, the test results exhibit that the MRDL model achieves 91.1%, 90.8%, and 91.6% accuracy on apple, citrus, and tomato disease databases, respectively compared to the classical models.

Plant Disease Detection and Solution System

Abstract: For preventing losses in the yield and quantity of the cultural product, Classification is performed, if proper analysis is not taken in this approach or classification, then it produces serious effects on plants and due to ich respective product quality or productivity is affected. Disease classification on the plants is very critical for supportable agriculture. It is very difficult to monitor or treat plant diseases manually. It requires a huge amount of work and also needs excessive processing time, therefore image processing for the detection of plant diseases. Automatic fruit disease detection and grading is a creative strategy.Bacterial Blight, Fruit Spot, Fruit Rot, and Virus Diseases on Fruits are the modules identified in this investigation.For the identification of diseases and their critical processes, including as photosynthesis, transpiration, pollination, fertilisation, germination, and some fruit diseases, molecular methods and profiling of volatile organic chemicals in plants are applied.The classification of plant diseases includes the processes of loading the image, pre-processing, segmenting, feature extraction, and SVM classifier.

Evaluation of Antifungal Activity from Bacillus subtilis strain AS80 Against Pathogenic Fungi Isolated from Hass Avocado Fruits

F ruit rot and anthracnose are the main diseases in avocado fruits caused by fungal species. Solving this problem with chemical reagents has led to human health and pollution problems. Therefore, this study was aimed to select antagonistic bacteria to control those pathogenic fungi. The pathogenic fungi were isolated from avocado fruit occurred fruit rot or anthracnose symptoms. Based on morphological characteristics and the BLASTn results of sequences of the internal transcribed spacer of ribosomal DNA, the obtained fungal isolates belonged to three fungal genera, namely Fusarium, Lasiodiplodia and Colletotrichum, which was the most commonly occurring. Pathogenicity tests were evaluated on avocado fruit. Then the rhizosphere bacteria were isolated from the avocado rhizosphere. To study antagonistic activity, 101 bacterial isolates were cultured with five fungal pathogens using dual culture technique. The bacterial isolate AS80 exhibited high potential to against Fusarium sp. (61.7%), Lasiodiplodia sp. (66.7%) and Colletotrichum sp. (74.1%). The strain AS80 was used to evaluate the efficacy control of Fusarium sp. on “Hass” avocado fruit. The in vivo evaluation revealed that AS80 showed high efficacy against Fusarium sp. The 16s ribosomal DNA sequencing indicated that AS80 was similar to Bacillus subtilis (99.53 %). Further study under field conditions should be done to validate their efficacy.

Melatonin Treatment of Strawberry Fruit during Storage Extends Its Post-Harvest Quality and Reduces Infection Caused by Botrytis cinerea

Gray mold is a main disease of strawberry fruit (Fragaria × xananassa cv. Camino Real) caused by Botrytis cinerea, which leads to marketable value losses in the supply chain. The purpose of this study was to investigate the effects of exogenous melatonin (MT) on the physicochemical quality, antioxidant defense system, and disease resistance of strawberry fruit to B. cinerea infection. The results revealed that strawberry fruit immersed in 100 µM MT for 15 min effectively maintained its brightness and delayed the change in fruit color. MT also maintained the level of titratable acidity and slowed down the increase of total soluble solids in strawberry fruit. Moreover, strawberries immersed in MT maintained a fresh weight and fruit firmness, as well as reduced B. cinerea infection when compared to the untreated control fruit and fruit treated with 5% NaOCl. In addition, MT increased the accumulation of DPPH scavenging capacity and the activity of antioxidant enzymes (SOD, POD, and APX) with the exception of CAT. The same effect was also observed in strawberry fruit after immersion in MT and followed by B. cinerea inoculation. These findings demonstrated that exogenous MT could effectively maintain the postharvest quality of strawberries, even when the fruit was inoculated with B. cinerea.

Relationships between fungal diversity and fruit quality of Yuluxiang pear during low temperature storage.

Postharvest decay is an urgent problem that affects the storage of pears. Low temperature storage is one of the most important methods to reduce the prevalence of fruit diseases during storage. In this study, the microbial diversity of postharvest Yuluxiang pear (Pyrus × michauxii "Yu Lu Xiang") fruits stored at low temperature for different lengths of times was analyzed. Illumina MiSeq high-throughput sequencing was used to analyze the composition and diversity of fungal communities. The results showed that the fungi within fruit were classified into 6 phyla, 18 classes, 40 orders, 72 families, and 92 genera based on the 97% sequence similarity level. They belonged to 6 phyla, 18 classes, 40 orders, 72 families, and 92 genera. The highest richness of fungi was obtained after 30 d of treatment. The β-diversity index showed that the fungal community composition of these fruit was significantly different at the beginning of storage compared with the different timepoints of samples at low temperature during storage. The comparison of fungal composition at the phylum level indicated that Ascomycota was dominant in the different timepoints of samples at low temperature, while Alternaria was the primary fungus at the genus level. A correlation analysis was used to further explore the correlation between fungi and fruit firmness, titratable acid, and solid soluble contents at low temperatures during storage. Aureobasidium and Didymella positively correlated with the soluble solids and hardness. Phoma positively correlated with the titratable acid, and Aspergillus positively correlated with titratable acid and hardness. This study can guide the industrial production of Yulu pear and also provide a theoretical basis to prevent and control diseases during the storage period of Yulu pear.

Postharvest Biology and Technology of Loquat (Eriobotrya japonica Lindl.)

Loquat (Eriobotrya japonica Lindl.) fruit is a rich source of carotenoids, flavonoids, phenolics, sugars, and organic acids. Although it is classified as a non-climacteric fruit, susceptibility to mechanical and physical bruising causes its rapid deterioration by moisture loss and postharvest decay caused by pathogens. Anthracnose, canker, and purple spot are the most prevalent postharvest diseases of loquat fruit. Cold storage has been used for quality management of loquat fruit, but the susceptibility of some cultivars to chilling injury (CI) consequently leads to browning and other disorders. Various techniques, including cold storage, controlled atmosphere storage, hypobaric storage, modified atmosphere packaging, low-temperature conditioning, heat treatment, edible coatings, and postharvest chemical application, have been tested to extend shelf life, mitigate chilling injury, and quality preservation. This review comprehensively focuses on the recent advances in the postharvest physiology and technology of loquat fruit, such as harvest maturity, fruit ripening physiology, postharvest storage techniques, and physiological disorders and diseases.

Efficacy of new generation oomycete-specific fungicides on life stages of Phytophthora meadii and field evaluation through bunch spraying system

Fruit rot disease (FRD) of arecanut, caused by Phytophthora meadii, is an important fruit disease of this palm tree that resulted in huge economic losses to the growers in India. In recent years, the control of this disease has become a prime factor in the management of arecanut plantations. Though prophylactic sprayings of Bordeaux mixture (1%) along with other older fungicides are useful in reducing the disease severity. Hence, there is an urgent need for new generation molecules to combat FRD under field conditions. The present investigation was aimed at evaluating newer oomycete-specific fungicides in in-vitro on different life stages of Phytophthora and in-vivo through a Bunch Spraying System (BSS) from ground level. The pathogen was isolated, identified, and characterized from varied regions and one virulent isolate from each region was used. Out of the 11 fungicides tested, EC50 for mycelial inhibition among isolates was lowest in Famoxadone + Cymoxanil. Similarly, the lowest EC50 for sporangial production was recorded in Iprovalicarb + Propineb, Famoxadone + Cymoxanil, and Kresoxymethyl ranging from 210.70 to 517.87 mg mL_1. The most effective fungicide for inhibition of zoospore release was Dimethomorph + Mancozeb which ranged from 406.81 to 565.80 mg mL_1. Bunch spraying of fungicides such as Bordeaux mixture (1%), mandipropamid (0.5%), fosetyl-Al (0.3%), and a combination of metalaxyl-mancozeb (0.2%) from ground level had a significant (P < 0.05) effect against FRD. These fungicides were found most effective in reducing the disease up to an extent of 65–70% and which in turn increased the dry nut yield by 75–95% when applied twice compared to untreated control. However, a semi-systemic fungicide mandipropamid could be a potential alternative to the Bordeaux mixture for effective control of FRD under field conditions.